I am finding and plotting local maximas and minimas on a waveform with the function findpeaks. I would like to be able to select some of those peaks with a pointer directly from the plot and get the coordinates into the workspace.
Is that possible?
Here is a subset of an example dataset:
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prominence_factor_localp2p = 0.0000004;
figure;
subplot(2,1,1)
findpeaks (data,'MinPeakProminence', prominence_factor_localp2p);
subplot(2,1,2)
findpeaks (-data,'MinPeakProminence', prominence_factor_localp2p);
Try
[x,y] = ginput(1) % Returns x and y after one mouse click
if you want to get one peak or:
[X,Y] = ginput() % Returns X=[x1..xN] and Y=[y1..yN] after N clicks, stop with ENTER
if you want to get multiple peaks in vector format
Unfortunately, I don't have the Signal Processing Toolbox (findpeaks is part of the SPT) so I'll answer this without it.
Say you have a function:
x = sin(linspace(0, 2*pi, 1000)) + 0.1*rand(1, 1000);
plot(linspace(0, 2*pi, 1000),x);
This gives be the following plot:
Now, using the function "Data Cursor" ,
you can select a point on the plot by clicking at it. You can drag the data tip around if you didn't hit the correct point at the first try. If you right click on the frame that comes up, you can export the [x,y] values to the workspace:
This gives the following variable (struct) in the workspace:
peak_value_1
peak_value_1 =
Target: [1x1 Line]
Position: [1.5849 1.0984]
DataIndex: 253
Now you have the positions of the maximum point:
position = peak_value_1.Position
position =
1.5849 1.0984
How you want to proceed from here is your call. Note that you can create multiple data tips by holding the Shift button while clicking.
Related
I am working on a signal. The problem I am facing is that when I apply FFT at a higher resolution, the results are distorted or inaccurate.
% This is the Signal
ppg=[112.876329616814
112.658408873981
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% plotting frequency domain
plot(abs(fft(ppg,1024)));
the result i get for 1024 point resolution is,
% plotting frequency domain
plot(abs(fft(ppg,2048)));
the result I get for 2048 point resolution is,
In my knowledge, increasing resolution does not distort the fft result. If someone knows why is this happening please let me know.
Note: I am using property editor from figure window to zoom out my results.
fft(ppg,2048) pads ppg with zeros to make it 2048 elements long, then applies the FFT. Padding your signal with zeros is bad because it introduces a big jump, your signal is all close to 112. This jump will influence the output of the FFT much more than the actual data.
If you want to increase the resolution of the frequency domain that you compute, you will have to sample your signal for longer. There are no shortcuts.
I have points that are all part of a spherical surface. How can I create a 3D sphere where the color of the sphere is determined by the density of the points (smoothed). An example of data points can be found in the picture below.
Using the following code, the points can be colored:
x = data(:,1);
y = data(:,2);
z = data(:,3);
D = [x(:), y(:), z(:)];
N = numel(x);
%// calculation of color vector
[n,m] = ndgrid(1:N,1:N);
%// euclidian distance of each point to every other point
X = arrayfun(#(a,b) sum( (D(a,:) - D(b,:)).^2 ), n, m);
%// threshold factor
T = 1;
%// sort distances of points
Y = sort(X,2);
%// calculate average distance of the closest T% of all points
Z = mean(Y(:,2:ceil(N*T)),2);
%// plot
colormap jet;
scatter3(x,y,z,20,-Z,'filled');
title('T = 0.01')
Now, I want to color a sphere according to the data. The following figure is for random data.
[x,y,z] = sphere;
surf(x,y,z,rand(length(x)));
colormap jet
shading interp
Sample of my data:
-0.636016480755703 0.617525876796302 -0.0928047432418846
-0.973951523685005 1.33968621140501 -0.484260283616615
-1.09449677739217 1.95314823996034 -0.997620228061477
-1.27650273224044 2.30054644808743 -1.52076502732240
-1.34107124912069 2.50643151442066 -1.93523263993568
-1.41743718592965 2.64326633165829 -2.38693467336683
-1.52722674072605 2.66172386431264 -2.68924816504662
-1.78737177571955 2.53918932377253 -2.86176675629917
-2.13798636181308 2.25411151223426 -2.71760930605696
-2.63246062794664 1.72971210753335 -2.72474671481593
-3.03187531422826 1.12946204122675 -3.07732528909000
-3.24477552244776 0.394710528947106 -3.67518248175182
2.78947368421053 1.11300309597523 -4.46904024767802
2.49650108417110 1.17716341415336 -4.93987778434851
2.52268839923534 0.940134822416742 -5.07883086829661
2.87130058385343 0.507398832293135 -4.76887457217636
3.04415584415584 0.461038961038961 -4.41298701298701
3.09087249672940 0.653567475093087 -4.11894938110094
3.11987397479496 0.702540508101620 -3.94573914782957
3.17966101694915 0.719840478564307 -3.52233300099701
3.12836149155253 0.840997700689793 -2.86519044286714
2.97330943133154 0.892490787770142 -2.26048202370282
2.81690697215090 0.873000197511357 -1.86114951609718
2.72014039944631 0.816195372750643 -1.64094324698438
2.50647023691021 0.872387019709337 -1.35715707744376
2.23888664376642 0.836886239644373 -1.02939987876339
1.96850235730765 0.814575183067509 -0.776808105125891
1.64841095342794 1.11333200079952 -0.690885468718768
1.36944528036914 1.18331828668874 -0.567609589728157
0.920234429323533 0.813251216847125 -0.225489222211184
0.570574643359454 0.388738195700221 -0.0264215390797675
0.316863696069516 -0.0561281196322118 0.0646660604223506
0.338646811912852 -0.391515090945433 0.0651609034579250
0.479434319290907 -0.676526242406135 0.0231052683995618
0.505991285403050 -0.746187363834423 0.00925925925925952
0.399658325796402 -0.813636820420058 0.0130640136669684
0.182226660009985 -0.957613579630554 0.00439340988517190
-0.0248032672576950 -1.24863034166750 -0.0676860245044320
-0.283441074092491 -1.72710094480358 -0.272948781700647
-0.527511004401761 -2.34133653461385 -0.705782312925170
-0.797852242219350 -2.97176096251367 -1.49487918862484
-0.922330097087379 -3.29166249624662 -2.23876488839956
-0.898067487734055 -3.46104936417343 -3.16261139481326
-0.727430211839240 -3.46159176400713 -3.78058800237577
-0.614893829129698 -3.34522978765826 -4.33002691655867
-0.453940686573228 -3.06104001625025 -4.98694901482836
-0.173647905628312 -2.72118364490653 -5.48340497850645
0.0242345666699911 -2.38655629799541 -5.81115986835544
0.198836859520706 -2.10383034192319 -6.01564223403189
0.380042037834051 -1.79871884696227 -6.17951156040436
0.423617429986857 -1.63856030735012 -6.25290668284299
0.368721000605205 -1.66920516441396 -6.24581400040347
0.0171154038634771 -1.99409468521670 -6.09303373035732
-0.396368687369779 -2.45550153785098 -5.72055759499951
-0.911024174942322 -3.02593038419099 -4.85911325107834
-1.22442557442557 -3.29275724275724 -3.85614385614386
-1.22364472894579 -3.30446089217844 -2.70414082816563
-1.09318766066838 -3.01586909234724 -1.74006327862369
-0.846371252649642 -2.61244574543252 -1.05284142525487
-0.594202898550724 -2.24637681159420 -0.644927536231885
-0.493466023321271 -2.07438681141938 -0.501708886208283
-0.414079822616408 -1.88802660753880 -0.374168514412417
-0.0486402719456110 -1.25204959008198 -0.0690361927614474
0.514052222443692 -0.238489136934423 0.0455451465018948
1.25832163625426 0.215410066172047 -0.196310407058352
1.72030784508441 0.633813306852036 -0.532571996027806
2.33757173956066 1.28933306946368 -1.43583019988126
2.66762105686156 1.66294956801286 -2.65888085191883
2.82720953326713 1.42879841112215 -3.80993048659384
2.70761349939735 1.02732020891924 -4.72047006830052
2.42173094081491 0.500297412511153 -5.41731932189947
1.64370927318296 -0.734636591478697 -6.11152882205514
1.19525675811476 -1.17174153351422 -6.22434931162697
1.11648548917922 -1.26179315847213 -6.22569063528473
1.11648548917922 -1.26179315847213 -6.22569063528473
1.29463307776561 -1.04600219058050 -6.21905805038335
1.69427680547174 -0.494216455441561 -6.11265338966003
2.19971642697995 0.369252582540004 -5.67956248734049
2.63406087304766 1.03103724469363 -4.84551461754105
2.90801393728223 1.36689895470383 -3.48257839721254
2.69187842551071 1.30109616342800 -2.03637269556552
2.04063692987744 0.843078159533856 -0.848754269640346
1.28362077559565 0.0458578406938491 -0.185724254810089
0.722807017543860 -0.518245614035088 -0.00491228070175431
0.548188515490968 -0.832172772227268 -0.0118579069532743
0.489908530522967 -1.08401272618811 -0.0579140982302633
0.485282298573438 -1.30887080570625 -0.124573035965441
0.674118231495281 -1.33253849975161 -0.168007948335817
0.910319782104308 -1.33229093110057 -0.229244426510643
1.52194752774975 -1.40302724520686 -0.515186680121089
1.94507084414289 -1.55647575334265 -0.876222310915985
2.35918818446699 -1.89234401687933 -1.55827388727017
2.71365858525392 -2.06993913997805 -2.58001596328445
2.86434225027552 -1.95721871555956 -3.17287846909127
2.85724240915879 -1.92110502737680 -3.66057740169238
2.87056949422541 -1.78156113102350 -3.98426921545201
2.87284396309667 -1.61111111111111 -4.25952667468913
2.80383257690368 -1.63519919314170 -4.40963187090267
2.74593029062219 -1.74528113452512 -4.41146509537601
2.79961927662559 -1.78649433924456 -4.21245366195772
2.90093495126318 -1.80893176845037 -3.77849612094689
2.92225456735595 -1.85735796024895 -3.29276249749046
2.79813695871098 -1.99234642497482 -2.74043303121853
2.69918862065511 -1.87313432835821 -2.15235901031754
2.52209558088382 -1.58498300339932 -1.52319536092781
2.00474364150182 -1.47204279370206 -0.880904319741623
1.51878192927978 -1.62576379845738 -0.618351197034960
1.23150095123661 -1.63627716030840 -0.477520777010114
0.531772406847935 -1.78439073514602 -0.336606243705942
0.0184244597151679 -1.70859476147794 -0.250473060452145
-0.761328398519556 -1.39836951085326 -0.212463739121736
-1.14685385314615 -1.00161599838400 -0.209473790526209
-1.46421063169486 -0.401441585744319 -0.256982680949045
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3.32393239323932 -0.460796079607961 -3.07100710071007
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1.52950526524935 -0.148023047883966 -0.287701172263063
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In matlab, say I have a vector:
a = [0.001818443 0.002518386 0.003220336 0.005121008 0.005896566 0.006067186 0.006398329 0.006398407 0.008139209 0.008179847 0.009156658 0.010554859 0.010897468 0.011446512 0.011646556 0.013025077 0.013744086 0.014617856 0.014830682 0.014941674 0.015810817 0.015953685 0.016022438 0.01662184 0.017497373 0.018051816 0.018084908 0.019634522 0.02055418 0.021050675 0.021573997 0.022819828 0.024124407 0.02499767 0.025745151 0.026366919 0.029380223 0.029534435 0.029988118 0.033517171 0.037612906 0.038975473 0.045889922 0.04598939 0.045995714 0.046398796 0.047502087 0.048214192 0.050098857 0.053184072 0.055892719 0.057670042 0.059855042 0.061763503 0.065288778 0.066057267 0.066842804 0.067799739 0.069549949 0.070151584 0.071572852 0.084351815 0.084676596 0.088092878 0.088329724 0.089958848 0.09000399 0.092272165 0.092561834 0.092888091 0.093193395 0.095380669 0.100645564 0.101506295 0.104656067 0.105057051 0.10527394 0.107024689 0.107608649 0.108699789 0.109433298 0.111805635 0.111990726 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715.6820763 716.5968312 716.748184 718.3387661 722.6523124 729.8391509 729.9603565 738.1141906 740.0781311 740.9359117 743.2016098 746.0610388 746.9304326 751.2793689 762.8213655 776.0875421 776.95767 782.0872564 786.4032758 797.0495954 802.3780486 807.0296451 808.4134688 810.8108108 816.0323573 816.4978119 823.8885202 826.5147869 827.2487539 831.590189 834.348693 838.3354074 838.3589181 838.4725936 841.2263536 841.4541433 842.192656 849.8034891 850.9535395 854.6521102 856.3480597 860.9894219 861.2777715 867.731809 871.7094202 872.0127878 873.9274205 874.8131969 877.5821738 883.9551347 885.7897929 886.6123515 895.1637275 897.7273744 901.8215742 904.5114863 911.8290271 914.9009406 915.7225753 918.8056513 919.4782268 929.4124233 936.3934569 937.1626184 941.5547644 951.3016066 952.2462556 960.4722946 969.9117367 971.8824626 972.9233379 976.9839367 977.0776597 981.6542477 981.9170028 982.1510719 982.6343189 991.1366503 996.2903501 999.3212528 1001.832921 1003.265814 1008.174158 1008.72466 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1374.224267 1374.426821 1376.090291 1376.767579 1377.709222 1378.992275 1386.34268 1393.237678 1395.764639 1399.046874 1403.381881 1409.649378 1409.764125 1416.008286 1418.132612 1420.75316 1422.064666 1431.052952 1432.217811 1433.785163 1440.760197 1444.829639 1444.973466 1454.365041 1456.299203 1462.53896 1464.775301 1465.840677 1467.512507 1474.858813 1475.138297 1476.249229 1476.272364 1480.023617 1482.224389 1486.00906 1491.764706 1493.101858 1494.370522 1497.375219 1500.214533 1501.058681 1505.500869 1505.855949 1506.72917 1508.678238 1508.848184 1508.957919 1511.338003 1513.778247 1515.673848 1517.282454 1517.801833 1525.706865 1526.162727 1527.398904 1529.231867 1532.500663 1535.63675 1538.160776 1550.196 1551.415908 1554.589619 1557.886322 1565.729567 1567.652141 1573.937574 1580.029757 1593.784378 1597.864491 1604.245393 1607.572744 1607.952827 1608.004008 1608.949155 1615.258382 1615.593876 1616.511864 1617.487798 1636.488051 1636.54517 1643.678591 1645.21835 1645.335513 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1920.950517 1926.326659 1928.176102 1929.506964 1934.604217 1939.777123 1939.9775 1941.755309 1943.528118 1944.940437 1948.146898 1949.393129 1952.669934 1957.382105 1974.814187 1974.930052 1977.787028 1978.05484 1981.278578 1985.544084 1985.951329 1987.672333 1989.859323 1999.003701 2000.29839 2010.240822 2011.18677 2013.788559 2015.608553 2017.241148 2018.726592 2023.237331 2024.367796 2025.012118 2030.088672 2030.858289 2031.91155 2047.429465 2056.103201 2060.681174 2067.853485 2068.090404 2070.455076 2074.196306 2075.368651 2079.204847 2085.470085 2085.729643 2088.787981 2090.90702 2096.795218 2098.107784 2109.1462 2111.881475 2112.3375 2119.125894 2132.544339 2134.309156 2137.225421 2137.34022 2140.171403 2141.529288 2150.369762 2151.661726 2154.312051 2155.000962 2156.770678 2157.759589 2164.041693 2164.805817 2165.059708 2168.65522 2169.206429 2174.040541 2188.917693 2192.494984 2208.212818 2208.768799 2216.977084 2218.692144 2220.102318 2230.953269 2234.154411 2234.405244 2235.065111 2236.344979 2249.802239 2264.686865 2267.396929 2273.404114 2273.754356 2277.413755 2280.6782 2283.149105 2285.348922 2289.328316 2290.734348 2295.517396 2312.503918 2320.990391 2322.061912 2323.440401 2324.878674 2333.165823 2333.252925 2335.603857 2337.325547 2345.946966 2358.273812 2366.02324 2370.471418 2371.784879 2375.909149 2379.075768 2385.552289 2389.641257 2389.86403 2390.725414 2395.819447 2407.106186 2408.175752 2429.088981 2434.82175 2440.124058 2467.929505 2471.566345 2477.609812 2489.945091 2491.580836 2510.302527 2511.638942 2515.044217 2515.71574 2517.028608 2524.354087 2524.877922 2526.06623 2535.558951 2535.721585 2536.492167 2537.325694 2537.709872 2539.365845 2540.281295 2553.669496 2558.765222 2571.722037 2572.527088 2574.079989 2582.056893 2582.866113 2588.746023 2591.215869 2599.739431 2608.250835 2609.567659 2609.624241 2610.649666 2619.595179 2621.563198 2636.421069 2639.394226 2642.023428 2669.445731 2675.382826 2680.034969 2694.084625 2696.268191 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3811.771546 3814.024695 3867.8375 3883.205185 3886.970119 3908.597606 3911.469436 3917.313319 3939.971862 3986.038094 3987.670344 4046.750127 4066.433675 4092.504341 4097.021961 4169.546188 4186.34036 4187.66536 4190.45858 4204.426559 4212.053484 4243.227528 4250.384263 4254.988812 4260.547742 4262.13353 4320.226864 4367.875314 4388.094236 4536.069442 4564.327703 4567.306728 4604.70907 4646.504789 4671.757915 4699.991441 4787.618259 4876.00814 4904.917446 4917.17524 4925.327908 5011.724579 5098.552384 5303.654354 5308.235953 5309.20718 5392.941707 5419.906687 5475.854044 5495.805466 5568.353474 5640.966362 5729.170599 5756.300338 5806.041122 5832.62891 5835.703258 5915.919707 5927.430005 5981.107598 6030.061892 6096.21919 6167.676768 6201.442974 6225.328106 6260.287897 6289.796644 6322.660099 6326.143981 6469.370471 6476.395452 6499.135987 6644.829529 7103.246168 7336.643496 7450.887574 7463.63355 7724.153705 8125.302957 8315.141568 8480.871611 8667.155784 8993.192971 10269.69361 11689.13634 12457.90885 12725.48318 12877.43593];
I want to split a into ~10 discrete groups based on value to make a grouped boxplot of:
data = rand(2348,1);
so that:
boxplot(data,group)
The discrete groups could be like the x-axis in this plot:
Let's say we split into 10 groups by ascending order of values. Try this:
%Note I added 2 extra zero values to start of this matrix to make it divisible by 10
a = [0.000 0.000 0.001818443 0.002518386 0.003220336 0.005121008 0.005896566 0.006067186 0.006398329 0.006398407 0.008139209 0.008179847 0.009156658 0.010554859 0.010897468 0.011446512 0.011646556 0.013025077 0.013744086 0.014617856 0.014830682 0.014941674 0.015810817 0.015953685 0.016022438 0.01662184 0.017497373 0.018051816 0.018084908 0.019634522 0.02055418 0.021050675 0.021573997 0.022819828 0.024124407 0.02499767 0.025745151 0.026366919 0.029380223 0.029534435 0.029988118 0.033517171 0.037612906 0.038975473 0.045889922 0.04598939 0.045995714 0.046398796 0.047502087 0.048214192 0.050098857 0.053184072 0.055892719 0.057670042 0.059855042 0.061763503 0.065288778 0.066057267 0.066842804 0.067799739 0.069549949 0.070151584 0.071572852 0.084351815 0.084676596 0.088092878 0.088329724 0.089958848 0.09000399 0.092272165 0.092561834 0.092888091 0.093193395 0.095380669 0.100645564 0.101506295 0.104656067 0.105057051 0.10527394 0.107024689 0.107608649 0.108699789 0.109433298 0.111805635 0.111990726 0.112119163 0.113570537 0.115032624 0.123301615 0.125012672 0.127758465 0.131636854 0.132397883 0.132910662 0.136185494 0.137039002 0.138037293 0.139764132 0.140727482 0.141044291 0.141523184 0.142202565 0.142563209 0.145192227 0.146881752 0.149407941 0.152043489 0.153144103 0.153181689 0.153795372 0.15548845 0.158134807 0.159905274 0.160042269 0.160098768 0.160483614 0.164710118 0.166850893 0.167909098 0.167986172 0.169019205 0.173698541 0.174264483 0.17696023 0.177973442 0.182348008 0.192484859 0.193880575 0.197216088 0.197939827 0.198109045 0.199497862 0.200821988 0.203783239 0.20515055 0.206573438 0.207185798 0.209268239 0.209386896 0.210951877 0.212023024 0.213363487 0.214391326 0.221532866 0.223109522 0.225343507 0.22641709 0.228343987 0.229206318 0.231114414 0.234752015 0.237026193 0.237716285 0.240721044 0.242380638 0.245407553 0.246434245 0.247559843 0.247849238 0.253027915 0.256495379 0.257901113 0.258536851 0.259306669 0.259722973 0.269672307 0.269866791 0.277255751 0.282296038 0.283236904 0.286946602 0.290243971 0.291043929 0.29129401 0.295039384 0.306007647 0.318012708 0.31816788 0.323432941 0.327635294 0.331093206 0.332249017 0.336175038 0.338095934 0.34029032 0.34317957 0.343788501 0.344121892 0.354931564 0.35667793 0.363077884 0.366887155 0.367370204 0.368269666 0.368423655 0.372253797 0.373533628 0.376022623 0.380837432 0.38261496 0.38391646 0.387548982 0.390389207 0.391454753 0.392089937 0.393426643 0.399546308 0.400245613 0.410202767 0.410776868 0.411723243 0.413456921 0.415884043 0.417789874 0.420313779 0.421429254 0.422511926 0.425439714 0.432455519 0.436032696 0.437367296 0.440152475 0.451378258 0.451755234 0.452195559 0.461256878 0.462486697 0.466794805 0.468274083 0.470176312 0.471656017 0.476690087 0.476869314 0.479601939 0.480684241 0.48433634 0.48590973 0.487749692 0.488207469 0.492988875 0.494796745 0.498156249 0.4985104 0.504612947 0.504967424 0.50679421 0.507507695 0.508506011 0.509330529 0.510055669 0.513319728 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1374.224267 1374.426821 1376.090291 1376.767579 1377.709222 1378.992275 1386.34268 1393.237678 1395.764639 1399.046874 1403.381881 1409.649378 1409.764125 1416.008286 1418.132612 1420.75316 1422.064666 1431.052952 1432.217811 1433.785163 1440.760197 1444.829639 1444.973466 1454.365041 1456.299203 1462.53896 1464.775301 1465.840677 1467.512507 1474.858813 1475.138297 1476.249229 1476.272364 1480.023617 1482.224389 1486.00906 1491.764706 1493.101858 1494.370522 1497.375219 1500.214533 1501.058681 1505.500869 1505.855949 1506.72917 1508.678238 1508.848184 1508.957919 1511.338003 1513.778247 1515.673848 1517.282454 1517.801833 1525.706865 1526.162727 1527.398904 1529.231867 1532.500663 1535.63675 1538.160776 1550.196 1551.415908 1554.589619 1557.886322 1565.729567 1567.652141 1573.937574 1580.029757 1593.784378 1597.864491 1604.245393 1607.572744 1607.952827 1608.004008 1608.949155 1615.258382 1615.593876 1616.511864 1617.487798 1636.488051 1636.54517 1643.678591 1645.21835 1645.335513 1646.530894 1649.071555 1654.143848 1655.068151 1659.690971 1667.482004 1668.764776 1677.231907 1678.43389 1680.018626 1681.080011 1681.642036 1686.215979 1693.028329 1696.574678 1697.26473 1699.010764 1699.50461 1699.574827 1699.889703 1703.539823 1704.893495 1705.346165 1708.078973 1708.857574 1711.671005 1712.28974 1718.32623 1720.538478 1730.582461 1730.697847 1733.562219 1737.854236 1742.26224 1744.92597 1746.791975 1749.73444 1749.806068 1754.604788 1760.3735 1763.940348 1778.185828 1781.402007 1782.452126 1783.059196 1783.494646 1791.479627 1793.032542 1796.056038 1796.581084 1810.67445 1811.996046 1814.322865 1815.332067 1818.201264 1820.767308 1826.482686 1828.233819 1830.732533 1830.877894 1836.531339 1836.535165 1838.751353 1849.003077 1852.535901 1856.165601 1856.421761 1856.605105 1858.371169 1862.783262 1863.240753 1866.161551 1876.872951 1877.844603 1881.280883 1884.118732 1890.465139 1891.273181 1902.445269 1902.90357 1905.020741 1910.565364 1911.111421 1918.625541 1920.950517 1926.326659 1928.176102 1929.506964 1934.604217 1939.777123 1939.9775 1941.755309 1943.528118 1944.940437 1948.146898 1949.393129 1952.669934 1957.382105 1974.814187 1974.930052 1977.787028 1978.05484 1981.278578 1985.544084 1985.951329 1987.672333 1989.859323 1999.003701 2000.29839 2010.240822 2011.18677 2013.788559 2015.608553 2017.241148 2018.726592 2023.237331 2024.367796 2025.012118 2030.088672 2030.858289 2031.91155 2047.429465 2056.103201 2060.681174 2067.853485 2068.090404 2070.455076 2074.196306 2075.368651 2079.204847 2085.470085 2085.729643 2088.787981 2090.90702 2096.795218 2098.107784 2109.1462 2111.881475 2112.3375 2119.125894 2132.544339 2134.309156 2137.225421 2137.34022 2140.171403 2141.529288 2150.369762 2151.661726 2154.312051 2155.000962 2156.770678 2157.759589 2164.041693 2164.805817 2165.059708 2168.65522 2169.206429 2174.040541 2188.917693 2192.494984 2208.212818 2208.768799 2216.977084 2218.692144 2220.102318 2230.953269 2234.154411 2234.405244 2235.065111 2236.344979 2249.802239 2264.686865 2267.396929 2273.404114 2273.754356 2277.413755 2280.6782 2283.149105 2285.348922 2289.328316 2290.734348 2295.517396 2312.503918 2320.990391 2322.061912 2323.440401 2324.878674 2333.165823 2333.252925 2335.603857 2337.325547 2345.946966 2358.273812 2366.02324 2370.471418 2371.784879 2375.909149 2379.075768 2385.552289 2389.641257 2389.86403 2390.725414 2395.819447 2407.106186 2408.175752 2429.088981 2434.82175 2440.124058 2467.929505 2471.566345 2477.609812 2489.945091 2491.580836 2510.302527 2511.638942 2515.044217 2515.71574 2517.028608 2524.354087 2524.877922 2526.06623 2535.558951 2535.721585 2536.492167 2537.325694 2537.709872 2539.365845 2540.281295 2553.669496 2558.765222 2571.722037 2572.527088 2574.079989 2582.056893 2582.866113 2588.746023 2591.215869 2599.739431 2608.250835 2609.567659 2609.624241 2610.649666 2619.595179 2621.563198 2636.421069 2639.394226 2642.023428 2669.445731 2675.382826 2680.034969 2694.084625 2696.268191 2704.531319 2707.839333 2716.792796 2730.732111 2732.069684 2737.677226 2778.443114 2782.215594 2785.874988 2791.253987 2791.436181 2801.164946 2805.848603 2806.178239 2810.666466 2813.901345 2830.859735 2853.498852 2856.717434 2868.888741 2870.367911 2878.874877 2883.703936 2885.632474 2905.874322 2907.515485 2916.389413 2923.073962 2929.712875 2931.019447 2933.791531 2933.930571 2935.077087 2949.087886 2976.158269 2981.768596 2983.915934 2989.715087 3001.266498 3002.479299 3011.896758 3011.912842 3020.089709 3025.493187 3042.22217 3043.797986 3044.370623 3045.683447 3053.071336 3054.37784 3059.479072 3063.92801 3107.161718 3151.462292 3173.531554 3256.077437 3256.892854 3259.605488 3265.533651 3289.866956 3319.895402 3333.730546 3378.930836 3388.87019 3396.586658 3408.947451 3436.547313 3439.845643 3464.238962 3465.187872 3465.352967 3498.880213 3522.537563 3533.001912 3553.327338 3600.815901 3603.355282 3717.619142 3755.870625 3760.009184 3773.018383 3783.863253 3811.612746 3811.771546 3814.024695 3867.8375 3883.205185 3886.970119 3908.597606 3911.469436 3917.313319 3939.971862 3986.038094 3987.670344 4046.750127 4066.433675 4092.504341 4097.021961 4169.546188 4186.34036 4187.66536 4190.45858 4204.426559 4212.053484 4243.227528 4250.384263 4254.988812 4260.547742 4262.13353 4320.226864 4367.875314 4388.094236 4536.069442 4564.327703 4567.306728 4604.70907 4646.504789 4671.757915 4699.991441 4787.618259 4876.00814 4904.917446 4917.17524 4925.327908 5011.724579 5098.552384 5303.654354 5308.235953 5309.20718 5392.941707 5419.906687 5475.854044 5495.805466 5568.353474 5640.966362 5729.170599 5756.300338 5806.041122 5832.62891 5835.703258 5915.919707 5927.430005 5981.107598 6030.061892 6096.21919 6167.676768 6201.442974 6225.328106 6260.287897 6289.796644 6322.660099 6326.143981 6469.370471 6476.395452 6499.135987 6644.829529 7103.246168 7336.643496 7450.887574 7463.63355 7724.153705 8125.302957 8315.141568 8480.871611 8667.155784 8993.192971 10269.69361 11689.13634 12457.90885 12725.48318 12877.43593];
%ascending order sort
a = sort(a);
%split into 10.
data = reshape(a,235,10);
%boxplot
boxplot(data(:,1:10))
Produces this:
You can compare the values of a with their quantiles to generate groups with similar sizes. This approch automatically handles the case when the size of a is not a multiple of the number of groups.
N = 10; % desired number of groups
thresholds = quantile(a, 0:1/N:1-1/N); % for approximately equal-size groups
group = sum(bsxfun(#ge, a, thresholds.'), 1); % this ranges from 1 to N
For your example a and data, this gives the following group sizes:
>> sum(bsxfun(#eq, group(:), 1:N), 1)
ans =
235 235 234 235 235 235 235 234 235 235
To do the plot, you probably want to use the average of each group as the x-axis value:
a_average_group = accumarray(group(:), a(:), [], #mean);
boxplot(data, a_average_group(group))
produces
Some way to group the data automatically is to use hist. The elements in a are sorted into 10 equally spaced bins along the x-axis between the minimum and maximum values of a. As hist returns the center of the bins, there is some calulation to get the right border of the bin, so one can calculate the correct bin given some value of a. In your example the 8th bin has no values though, resulting in only 9 boxplots drawn.
a = [0.001818443 0.002518386 0.003220336 0.005121008 0.005896566 0.006067186 0.006398329 0.006398407 0.008139209 0.008179847 0.009156658 0.010554859 0.010897468 0.011446512 0.011646556 0.013025077 0.013744086 0.014617856 0.014830682 0.014941674 0.015810817 0.015953685 0.016022438 0.01662184 0.017497373 0.018051816 0.018084908 0.019634522 0.02055418 0.021050675 0.021573997 0.022819828 0.024124407 0.02499767 0.025745151 0.026366919 0.029380223 0.029534435 0.029988118 0.033517171 0.037612906 0.038975473 0.045889922 0.04598939 0.045995714 0.046398796 0.047502087 0.048214192 0.050098857 0.053184072 0.055892719 0.057670042 0.059855042 0.061763503 0.065288778 0.066057267 0.066842804 0.067799739 0.069549949 0.070151584 0.071572852 0.084351815 0.084676596 0.088092878 0.088329724 0.089958848 0.09000399 0.092272165 0.092561834 0.092888091 0.093193395 0.095380669 0.100645564 0.101506295 0.104656067 0.105057051 0.10527394 0.107024689 0.107608649 0.108699789 0.109433298 0.111805635 0.111990726 0.112119163 0.113570537 0.115032624 0.123301615 0.125012672 0.127758465 0.131636854 0.132397883 0.132910662 0.136185494 0.137039002 0.138037293 0.139764132 0.140727482 0.141044291 0.141523184 0.142202565 0.142563209 0.145192227 0.146881752 0.149407941 0.152043489 0.153144103 0.153181689 0.153795372 0.15548845 0.158134807 0.159905274 0.160042269 0.160098768 0.160483614 0.164710118 0.166850893 0.167909098 0.167986172 0.169019205 0.173698541 0.174264483 0.17696023 0.177973442 0.182348008 0.192484859 0.193880575 0.197216088 0.197939827 0.198109045 0.199497862 0.200821988 0.203783239 0.20515055 0.206573438 0.207185798 0.209268239 0.209386896 0.210951877 0.212023024 0.213363487 0.214391326 0.221532866 0.223109522 0.225343507 0.22641709 0.228343987 0.229206318 0.231114414 0.234752015 0.237026193 0.237716285 0.240721044 0.242380638 0.245407553 0.246434245 0.247559843 0.247849238 0.253027915 0.256495379 0.257901113 0.258536851 0.259306669 0.259722973 0.269672307 0.269866791 0.277255751 0.282296038 0.283236904 0.286946602 0.290243971 0.291043929 0.29129401 0.295039384 0.306007647 0.318012708 0.31816788 0.323432941 0.327635294 0.331093206 0.332249017 0.336175038 0.338095934 0.34029032 0.34317957 0.343788501 0.344121892 0.354931564 0.35667793 0.363077884 0.366887155 0.367370204 0.368269666 0.368423655 0.372253797 0.373533628 0.376022623 0.380837432 0.38261496 0.38391646 0.387548982 0.390389207 0.391454753 0.392089937 0.393426643 0.399546308 0.400245613 0.410202767 0.410776868 0.411723243 0.413456921 0.415884043 0.417789874 0.420313779 0.421429254 0.422511926 0.425439714 0.432455519 0.436032696 0.437367296 0.440152475 0.451378258 0.451755234 0.452195559 0.461256878 0.462486697 0.466794805 0.468274083 0.470176312 0.471656017 0.476690087 0.476869314 0.479601939 0.480684241 0.48433634 0.48590973 0.487749692 0.488207469 0.492988875 0.494796745 0.498156249 0.4985104 0.504612947 0.504967424 0.50679421 0.507507695 0.508506011 0.509330529 0.510055669 0.513319728 0.52891378 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1.172495225 1.175475612 1.176864362 1.17990075 1.182195585 1.189691417 1.19404695 1.201722268 1.207506808 1.207712757 1.217276704 1.226244517 1.231233705 1.235338344 1.235488468 1.237856505 1.246471414 1.248198622 1.24847215 1.249213122 1.253941679 1.255492087 1.261797214 1.272565441 1.275217172 1.279047194 1.2941275 1.296036211 1.303184537 1.303538428 1.304022026 1.306154543 1.313038716 1.325574114 1.325811852 1.329512083 1.335354282 1.336243495 1.349582224 1.349879286 1.349900576 1.351984631 1.352752927 1.380875102 1.381652802 1.385006548 1.385551407 1.399529901 1.400418216 1.400665522 1.402213831 1.407079557 1.407902968 1.426432367 1.427988618 1.430494495 1.436726215 1.455773986 1.457812821 1.457839075 1.464415454 1.465676132 1.471725239 1.478228056 1.493616649 1.505911081 1.510317752 1.517723479 1.519844042 1.520079555 1.52266623 1.528263582 1.528956908 1.539259874 1.54540469 1.552334282 1.559284266 1.560271081 1.560397723 1.58015835 1.584258957 1.586824283 1.5901615 1.601497093 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1646.530894 1649.071555 1654.143848 1655.068151 1659.690971 1667.482004 1668.764776 1677.231907 1678.43389 1680.018626 1681.080011 1681.642036 1686.215979 1693.028329 1696.574678 1697.26473 1699.010764 1699.50461 1699.574827 1699.889703 1703.539823 1704.893495 1705.346165 1708.078973 1708.857574 1711.671005 1712.28974 1718.32623 1720.538478 1730.582461 1730.697847 1733.562219 1737.854236 1742.26224 1744.92597 1746.791975 1749.73444 1749.806068 1754.604788 1760.3735 1763.940348 1778.185828 1781.402007 1782.452126 1783.059196 1783.494646 1791.479627 1793.032542 1796.056038 1796.581084 1810.67445 1811.996046 1814.322865 1815.332067 1818.201264 1820.767308 1826.482686 1828.233819 1830.732533 1830.877894 1836.531339 1836.535165 1838.751353 1849.003077 1852.535901 1856.165601 1856.421761 1856.605105 1858.371169 1862.783262 1863.240753 1866.161551 1876.872951 1877.844603 1881.280883 1884.118732 1890.465139 1891.273181 1902.445269 1902.90357 1905.020741 1910.565364 1911.111421 1918.625541 1920.950517 1926.326659 1928.176102 1929.506964 1934.604217 1939.777123 1939.9775 1941.755309 1943.528118 1944.940437 1948.146898 1949.393129 1952.669934 1957.382105 1974.814187 1974.930052 1977.787028 1978.05484 1981.278578 1985.544084 1985.951329 1987.672333 1989.859323 1999.003701 2000.29839 2010.240822 2011.18677 2013.788559 2015.608553 2017.241148 2018.726592 2023.237331 2024.367796 2025.012118 2030.088672 2030.858289 2031.91155 2047.429465 2056.103201 2060.681174 2067.853485 2068.090404 2070.455076 2074.196306 2075.368651 2079.204847 2085.470085 2085.729643 2088.787981 2090.90702 2096.795218 2098.107784 2109.1462 2111.881475 2112.3375 2119.125894 2132.544339 2134.309156 2137.225421 2137.34022 2140.171403 2141.529288 2150.369762 2151.661726 2154.312051 2155.000962 2156.770678 2157.759589 2164.041693 2164.805817 2165.059708 2168.65522 2169.206429 2174.040541 2188.917693 2192.494984 2208.212818 2208.768799 2216.977084 2218.692144 2220.102318 2230.953269 2234.154411 2234.405244 2235.065111 2236.344979 2249.802239 2264.686865 2267.396929 2273.404114 2273.754356 2277.413755 2280.6782 2283.149105 2285.348922 2289.328316 2290.734348 2295.517396 2312.503918 2320.990391 2322.061912 2323.440401 2324.878674 2333.165823 2333.252925 2335.603857 2337.325547 2345.946966 2358.273812 2366.02324 2370.471418 2371.784879 2375.909149 2379.075768 2385.552289 2389.641257 2389.86403 2390.725414 2395.819447 2407.106186 2408.175752 2429.088981 2434.82175 2440.124058 2467.929505 2471.566345 2477.609812 2489.945091 2491.580836 2510.302527 2511.638942 2515.044217 2515.71574 2517.028608 2524.354087 2524.877922 2526.06623 2535.558951 2535.721585 2536.492167 2537.325694 2537.709872 2539.365845 2540.281295 2553.669496 2558.765222 2571.722037 2572.527088 2574.079989 2582.056893 2582.866113 2588.746023 2591.215869 2599.739431 2608.250835 2609.567659 2609.624241 2610.649666 2619.595179 2621.563198 2636.421069 2639.394226 2642.023428 2669.445731 2675.382826 2680.034969 2694.084625 2696.268191 2704.531319 2707.839333 2716.792796 2730.732111 2732.069684 2737.677226 2778.443114 2782.215594 2785.874988 2791.253987 2791.436181 2801.164946 2805.848603 2806.178239 2810.666466 2813.901345 2830.859735 2853.498852 2856.717434 2868.888741 2870.367911 2878.874877 2883.703936 2885.632474 2905.874322 2907.515485 2916.389413 2923.073962 2929.712875 2931.019447 2933.791531 2933.930571 2935.077087 2949.087886 2976.158269 2981.768596 2983.915934 2989.715087 3001.266498 3002.479299 3011.896758 3011.912842 3020.089709 3025.493187 3042.22217 3043.797986 3044.370623 3045.683447 3053.071336 3054.37784 3059.479072 3063.92801 3107.161718 3151.462292 3173.531554 3256.077437 3256.892854 3259.605488 3265.533651 3289.866956 3319.895402 3333.730546 3378.930836 3388.87019 3396.586658 3408.947451 3436.547313 3439.845643 3464.238962 3465.187872 3465.352967 3498.880213 3522.537563 3533.001912 3553.327338 3600.815901 3603.355282 3717.619142 3755.870625 3760.009184 3773.018383 3783.863253 3811.612746 3811.771546 3814.024695 3867.8375 3883.205185 3886.970119 3908.597606 3911.469436 3917.313319 3939.971862 3986.038094 3987.670344 4046.750127 4066.433675 4092.504341 4097.021961 4169.546188 4186.34036 4187.66536 4190.45858 4204.426559 4212.053484 4243.227528 4250.384263 4254.988812 4260.547742 4262.13353 4320.226864 4367.875314 4388.094236 4536.069442 4564.327703 4567.306728 4604.70907 4646.504789 4671.757915 4699.991441 4787.618259 4876.00814 4904.917446 4917.17524 4925.327908 5011.724579 5098.552384 5303.654354 5308.235953 5309.20718 5392.941707 5419.906687 5475.854044 5495.805466 5568.353474 5640.966362 5729.170599 5756.300338 5806.041122 5832.62891 5835.703258 5915.919707 5927.430005 5981.107598 6030.061892 6096.21919 6167.676768 6201.442974 6225.328106 6260.287897 6289.796644 6322.660099 6326.143981 6469.370471 6476.395452 6499.135987 6644.829529 7103.246168 7336.643496 7450.887574 7463.63355 7724.153705 8125.302957 8315.141568 8480.871611 8667.155784 8993.192971 10269.69361 11689.13634 12457.90885 12725.48318 12877.43593];
[counts,centers] = hist(a,10);
borders = centers+(centers(2)-centers(1))/2
b = arrayfun(#(x) sum(x>=borders),a);
boxplot(a,b)
I'm using MATLAB to plot a colormap of the following data matrix:
1010.89914200000 1006.07847500000 1013.91775300000 1016.37012500000 1012.64447500000 1005.15384200000 998.323644400000 1007.09643600000 1010.39007800000 1010.71070000000 1007.75920300000 1003.43986900000 1001.77407500000 1000.93290600000 1009.19935000000 1010.79651100000 1006.15733600000 1001.08001400000 1006.62765600000 1008.98760600000 1012.59690300000 1014.13669400000 1012.41850000000 1002.83265600000
1010.20939200000 1006.22354400000 1014.13985000000 1016.01628600000 1012.16700600000 1004.47184200000 1000.64279200000 1006.93063300000 1009.98950000000 1010.53409400000 1007.46695300000 1003.07056100000 1001.31949400000 1001.61572800000 1009.12864700000 1010.45935000000 1006.24603900000 1001.40907500000 1006.31782500000 1009.00493300000 1012.13883300000 1013.93106700000 1011.88797800000 1003.01553600000
1009.70062500000 1006.35064700000 1014.37573900000 1015.70891100000 1011.51357800000 1003.79413100000 1001.69951400000 1006.79389200000 1009.72253100000 1010.41560600000 1007.01026100000 1002.91738300000 1000.86708100000 1002.11736400000 1009.09675300000 1009.98591400000 1005.46058600000 1000.94756700000 1006.18716400000 1008.73213100000 1012.14396700000 1013.51734400000 1010.97627200000 1003.29271400000
1009.45768300000 1006.17825800000 1014.67340300000 1015.64428600000 1011.30645600000 1003.37367500000 1001.93843600000 1006.59857800000 1009.45626700000 1010.25717800000 1006.66668100000 1003.00867800000 1001.13924400000 1002.74437200000 1009.14411900000 1009.62172200000 1005.50861100000 1000.11247800000 1006.11126700000 1008.63767200000 1012.11852500000 1013.46424200000 1010.52458300000 1003.95781100000
1009.26808100000 1006.29626900000 1014.67797500000 1015.67235600000 1011.20240600000 1003.14341400000 1000.42042500000 1006.97025800000 1009.47529700000 1010.42883100000 1006.41034400000 1003.31582500000 1001.22851700000 1003.87331700000 1009.01971100000 1009.26751700000 1004.97643300000 1000.38995600000 1006.25921900000 1008.81359400000 1012.25596700000 1013.53560600000 1010.21200300000 1004.63438300000
1009.71863900000 1006.81711100000 1014.88478900000 1016.09375300000 1011.26197200000 1003.11559200000 1000.71963300000 1007.50932500000 1009.46868300000 1010.70578900000 1006.41695000000 1003.87943100000 1001.47584700000 1004.88967200000 1009.38281100000 1009.50196100000 1005.06519200000 1001.66275800000 1006.49482200000 1009.35829200000 1012.54210000000 1013.92888300000 1009.72913100000 1005.35431100000
1010.74544400000 1007.71330600000 1015.30482800000 1016.41307200000 1011.40723900000 1003.05097800000 1001.88330600000 1007.78023100000 1009.79253600000 1011.11156400000 1006.55320300000 1004.49287800000 1001.40507500000 1005.91256700000 1009.88450300000 1009.38280000000 1004.75816700000 1003.58816900000 1006.68395600000 1009.83212800000 1012.71196100000 1014.27383300000 1009.46791900000 1005.91156100000
1011.06202800000 1008.61448600000 1016.07176900000 1016.77051900000 1011.43023100000 1002.91816900000 1003.01835800000 1008.37585300000 1010.16145800000 1011.46680800000 1006.80956900000 1004.88291700000 1001.64883900000 1006.73743100000 1010.37819200000 1009.44031900000 1005.11520300000 1004.70793600000 1007.29316900000 1010.53632800000 1013.30822200000 1014.53464700000 1009.54564700000 1006.43934700000
1011.16811700000 1009.12379400000 1016.69230000000 1017.09807500000 1011.42089200000 1002.90685800000 1003.45940000000 1008.64450600000 1010.42875300000 1011.61208900000 1006.92791100000 1004.99500600000 1001.85114700000 1007.48185600000 1010.74164700000 1009.37652200000 1005.22774400000 1005.74404200000 1008.04547500000 1011.20978900000 1013.70315600000 1014.90081400000 1009.46251700000 1007.25164700000
1010.77128100000 1009.35747200000 1016.79156100000 1016.94504400000 1011.34709700000 1002.68326400000 1004.21865300000 1008.90464200000 1010.65171700000 1011.66855800000 1006.76375000000 1004.84766700000 1001.64799400000 1007.95280800000 1011.15295600000 1008.96945800000 1004.99150800000 1006.73475300000 1008.30754700000 1011.69105600000 1014.00060300000 1015.01862800000 1009.08597500000 1007.85208300000
1010.13805300000 1009.61241400000 1016.74593600000 1016.61859700000 1011.07230300000 1002.35865300000 1004.26001400000 1008.88295800000 1010.48621700000 1011.41217200000 1006.14741900000 1004.82872800000 1001.26854200000 1008.04161100000 1011.11477800000 1008.65341400000 1004.63091100000 1007.43303300000 1008.40434700000 1011.74642800000 1014.01016900000 1014.80443600000 1008.33869400000 1007.93218300000
1009.50911900000 1009.62698100000 1016.46591900000 1015.96478900000 1010.07972200000 1001.85613100000 1004.44510800000 1008.68885000000 1009.90488600000 1010.78808600000 1005.41067200000 1004.68175000000 1000.73121900000 1007.96492200000 1011.01123900000 1008.22990300000 1003.85685000000 1007.24613600000 1008.27287800000 1012.14434200000 1013.92860000000 1014.61665800000 1007.55034400000 1008.09293300000
1008.70381100000 1009.61384700000 1015.81295800000 1015.06458300000 1008.88961700000 1000.62531700000 1004.21893300000 1008.20705000000 1009.58456400000 1010.16761700000 1004.43428100000 1004.27616900000 1000.27990000000 1007.68135000000 1010.75977200000 1007.51076700000 1002.70041700000 1006.61412500000 1008.12120300000 1012.10416700000 1013.70059700000 1014.09623100000 1006.09171400000 1008.05956900000
1008.02154700000 1009.64861100000 1015.14255300000 1014.23098600000 1008.14283900000 999.389411100000 1004.11294400000 1008.03047200000 1009.17975600000 1009.66578900000 1003.65600000000 1003.73793600000 999.649786100000 1007.55710300000 1010.73914200000 1006.48525600000 1001.60153900000 1006.51005600000 1007.86194700000 1011.76237200000 1013.33892200000 1013.76143300000 1004.98931400000 1007.96544700000
1007.77482500000 1009.85345300000 1014.92648900000 1013.59322500000 1007.68484400000 998.743208300000 1004.23994200000 1008.15078900000 1009.14176900000 1009.13383600000 1003.04438300000 1003.35990600000 999.229216700000 1007.35725800000 1010.77036400000 1006.11508100000 1001.06650600000 1006.27331900000 1008.08580600000 1011.76860000000 1013.18307200000 1013.39113600000 1003.78306100000 1007.80175600000
1007.69477800000 1010.25384700000 1014.99210800000 1013.30303900000 1007.45265800000 998.250572200000 1004.45173600000 1008.31279400000 1009.06058100000 1008.82283300000 1002.55153300000 1003.10945300000 999.019630600000 1007.24711700000 1010.81812500000 1006.09366700000 1000.98814200000 1006.25510800000 1008.09595800000 1011.79827200000 1013.07516400000 1013.10823300000 1003.03183900000 1008.06458600000
1007.77405000000 1010.73199400000 1015.15546900000 1013.15583900000 1007.25787500000 997.884352800000 1004.75770600000 1008.85976700000 1009.25861700000 1008.55503600000 1002.43732200000 1002.93201900000 998.928380600000 1007.53712200000 1010.76891400000 1006.20278600000 1000.95717200000 1006.24851400000 1008.26927500000 1011.92516700000 1013.04778600000 1012.83340000000 1002.36345600000 1008.45907200000
1008.10153900000 1011.22165600000 1015.49348900000 1013.28646400000 1007.37516700000 997.841966700000 1005.30818900000 1009.36494400000 1009.81374200000 1008.59688100000 1002.46048900000 1003.12547200000 998.873250000000 1008.09001100000 1010.74253600000 1006.00015800000 1001.09626700000 1006.44443300000 1008.61596400000 1012.13335000000 1013.32301100000 1012.72540800000 1001.82905800000 1008.71992200000
1008.42932800000 1012.08600000000 1015.93560300000 1013.55619200000 1007.18396400000 997.877988900000 1005.97368300000 1009.70238900000 1010.35090600000 1008.72040000000 1002.82235000000 1003.50095000000 998.968997200000 1008.71467200000 1011.18516100000 1006.09722800000 1001.00105000000 1006.51150600000 1008.80134200000 1012.38964200000 1013.64155000000 1012.74316400000 1001.41934400000 1008.87543300000
1008.61755800000 1012.61210000000 1016.07700000000 1013.93586700000 1007.27577800000 997.712516700000 1006.77127200000 1010.00605300000 1010.65426700000 1008.88601400000 1003.20735600000 1003.72689700000 999.271758300000 1009.20620300000 1011.16123600000 1006.69687200000 1000.70609700000 1006.79953300000 1009.01541700000 1012.91482800000 1014.02131100000 1012.95065300000 1001.67870000000 1009.32203600000
1008.56708100000 1012.99515000000 1016.33867800000 1013.68418100000 1007.24658600000 997.281041700000 1007.01185000000 1010.30151400000 1010.94030600000 1008.70953300000 1003.34373100000 1004.04526700000 999.558302800000 1009.36840300000 1011.30540300000 1006.56111700000 1000.80576400000 1007.06003900000 1009.30639400000 1013.20931400000 1014.27723600000 1013.05665800000 1001.85187500000 1009.70395300000
1008.29791700000 1013.28623100000 1016.51517200000 1014.03927800000 1006.84327200000 997.159275000000 1007.09736400000 1010.48451100000 1010.96097800000 1008.46591400000 1003.29630300000 1003.91275300000 1000.09343100000 1009.50430800000 1011.42889700000 1006.72751400000 1000.51083900000 1007.10306100000 1009.37503100000 1013.39047200000 1014.59432200000 1013.03755800000 1002.26636900000 1010.06034200000
1008.21371700000 1013.59691400000 1016.65878900000 1013.99910800000 1006.30900300000 997.142713900000 1007.04279200000 1010.75180300000 1011.00974400000 1008.16542800000 1003.24316900000 1003.42274700000 1000.31632800000 1009.49489200000 1011.19880800000 1007.23048900000 1000.05682200000 1007.13264700000 1009.40641100000 1013.34435800000 1014.59523900000 1012.99997500000 1002.45651400000 1010.21388600000
1007.63143900000 1013.69220800000 1016.52085600000 1013.28099200000 1005.84439200000 997.479972200000 1007.22611700000 1010.59871900000 1010.82017800000 1007.92970300000 1003.35441900000 1002.36780800000 1000.54393300000 1009.14068600000 1011.02388300000 1007.05475600000 1000.35642800000 1006.99240300000 1009.16368100000 1013.13141400000 1014.49421400000 1012.86652200000 1002.60169400000 1010.12598900000
using:
imagesc(data)
Now I need to normalize each column separately in the following way: finding the maximum value of each column and set it's color, and finding the lowest value of each column and set it's color as well.
So in the end I need a colormap which have the same color for every local maximum and minimum of a column.
I'm quite new to plotting, so I tried looking for normalized colormaps here and on the web, but didn't find anything that can help me.
You're not going to be able to do this strictly with a colormap because the colormap is applied globally to the image and the color used for the local max in one column would be applied to all elements with that value regardless of whether they were the local max of their respective column.
Instead, you can normalize each column of your data and then display that.
%// Subtract off the minimum of each column
D = bsxfun(#minus, data, min(data, [], 1));
%// Divide by the maximum
D = bsxfun(#rdivide, D, max(D, [], 1));
%// Display the result
imagesc(D);
I'd like to make one period representative signal.
There are several signals in different periods.
I don't want to cut one period signal from several signals.
How can I solve this problem in matlab?
Below is the signal data values.
Thank you.
57.2336830000000
57.1587480000000
57.1025470000000
109.144632000000
110.081315000000
110.886862000000
111.580007000000
112.104549000000
112.497956000000
112.797694000000
112.947564000000
113.097433000000
113.134900000000
113.097433000000
113.022498000000
112.872629000000
112.629092000000
112.291886000000
111.917213000000
111.486339000000
110.980530000000
110.455988000000
109.856511000000
109.125899000000
108.357819000000
107.477337000000
106.559388000000
105.547771000000
104.536154000000
103.449602000000
102.344316000000
101.239031000000
100.189947000000
99.1221280000000
98.1479780000000
97.2112960000000
96.3120810000000
95.5440010000000
94.8321220000000
94.1951780000000
93.6331680000000
93.2022940000000
92.7714200000000
92.4342150000000
92.1532100000000
91.8909390000000
91.6848690000000
91.5349990000000
91.4038640000000
91.2539950000000
91.1603260000000
91.0666580000000
90.9729900000000
90.8231210000000
90.7669200000000
90.6357840000000
90.5421160000000
90.4297140000000
90.3173120000000
90.1487090000000
90.0175740000000
89.8302370000000
89.6991020000000
89.5117650000000
89.3244290000000
89.1370920000000
88.9497560000000
88.7249520000000
88.5376150000000
88.3315450000000
88.1442090000000
87.9381380000000
87.7320680000000
87.5072640000000
87.2824610000000
87.0763900000000
86.8515870000000
86.6267830000000
86.3645120000000
86.1584410000000
85.8961700000000
85.6713670000000
85.4278290000000
85.2217590000000
84.9782210000000
84.7346840000000
84.5098800000000
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If by "one period representative signal" you mean "get the average signal over all the periods", this is how.
This is what your data looks like:
If you know in advance how many cycles are in your signal (9 for your data above), then just reshape your signal into a 9x178 matrix (==numel(signal)/9) and find column means (ie a 1x178 matrix with the average signal).
nwaves = 9;
sig2 = reshape(sig,[numel(sig)/nwaves nwaves])';
avgSig = mean(sig2,1);
plot(avgSig);
If you don't know how many cycles in your signal...you could try doing the fourier transform, but it's not guaranteed...and if the number of data points isn't an exact multiple of the period length, then you'll have to modify the code to deal with that.
% get fourier transform
a = fft(sig);
% get period with max amplitude (but not period=0)
[val ix] = max(abs(a(2:end))) % don't include period=0
nwaves = ix + 1 % add 1 because of the offset above
% then calculate avg & plot as before with this `nwaves`.
(If you plot each 'cycle' though you'll notice that splitting into every 178 elements doesn't quite section your wave into parts from minimum to minimum - you might need to find a smarter way of doing that).